Drug Interactions in Outpatients.

Evaluation of a Drug Interactions Software (Interax-AI) in Outpatients.

Multiple morbidity is increasing, especially in elderly people, with a corresponding increase in polypharmacy and inappropriate prescriptions. According to different evaluations, between 25 and 75% of patients aged 75 or older are exposed to 5 or more drugs. There is increasing evidence that polypharmacy can cause more harm than good, especially in elderly people, due to factors such as drug-drug and drug-disease interactions.

Many strategies were proposed to reduce polypharmacy and inappropriate prescribing, but there is little evidence to show benefit. There is an urgent need to implement effective strategies. The application methodology must be simple so that it does not fail in daily practice.

For the current plan, an electronic medical record, named "DrApp", will be used, which will include a drug interaction program, (Interax-AI), which will automatically indicate the medication prescriptions that involve a risk for the patient.

All outpatient indications followed by physicians using the DrApp electronic history will be registered. The indications will be compared in the 4 months prior to the incorporation of the Interax-AI program with the 4 months after the incorporation of the program. Between both stages a period of 2 weeks will be established in which the data will not be recorded. The minimum & maximum number of patients that will be included in each stage are 100 & 200.

The primary end point is to compare the total number of indications per inpatient, before the availability of the Interax-AI program and after the application of this program.

The objective is to evaluate if the computer program of detection of drug interactions allows to limit the polypharmacy in outpatients.

Study Overview

• Status: Suspended
• Conditions: Polypharmacy; Drug Interaction; Adverse Drug Reaction; Outpatient
• Intervention / Treatment: Device: Interax-AI

Detailed Description

Multiple morbidity is increasing, especially in elderly people, with a corresponding increase in polypharmacy and inappropriate prescriptions. According to different evaluations, between 25 and 75% of patients aged 75 or older are exposed to 5 or more drugs. There is increasing evidence that polypharmacy can cause more harm than good, especially in elderly people, due to factors such as drug-drug and drug-disease interactions.

Many strategies were proposed to reduce polypharmacy and inappropriate prescribing, but there is little evidence to show benefit. There is an urgent need to implement effective strategies. The application methodology must be simple so that it does not fail in daily practice.

For the current plan, an electronic medical record, named "DrApp", will be used, which will include a drug interaction program, (Interax-AI), which will automatically indicate the medication prescriptions that involve a risk for the patient.

All outpatient indications followed by physicians using the DrApp electronic history will be registered. The indications will be compared in the 4 months prior to the incorporation of the Interax-AI program with the 4 months after the incorporation of the program. Between both stages a period of 2 weeks will be established in which the data will not be recorded. The minimum & maximum number of patients that will be included in each stage are 100 & 200.

The primary end point is to compare the total number of indications per inpatient, before the availability of the Interax-AI program and after the application of this program.

The objective is to evaluate if the computer program of detection of drug interactions allows to limit the polypharmacy in outpatients.

• Study Type: Interventional
• Enrollment (Anticipated): 200
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Argentina
  • Capital Federal
    • Ciudad Autonoma de Buenos Aire, Capital Federal, Argentina, C1121ABG
      • Centro de Vigilancia y Seguridad de Medicamentos
    • Ciudad Autonoma de Buenos Aire, Capital Federal, Argentina, C1121
      • Instituto de Investigaciones Cardiológicas Prof. Dr. Alberto C. Taquini
    • Ciudad autónoma de Buenos Aires, Capital Federal, Argentina, 1121
      • HOSPITAL DE CLINICAS JOSE DE SAN MARTIN

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Outpatients followed in outpatient clinics of doctors using the electronic medical record application DrApp

Exclusion Criteria:

• Lack of registration of medications used by the patient in the DrApp application

Study Plan

How is the study designed?

Design Details

• Primary Purpose: PREVENTION
• Allocation: NON_RANDOMIZED
• Interventional Model: SEQUENTIAL
• Masking: QUADRUPLE

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
NO_INTERVENTION: DrApp Without Interax-AI; There are approximately 100 outpatients in whom the indications were registered through the use of DrApp, before the implementation of the drug interactions detection module.
EXPERIMENTAL: DrApp With Interax-AI; There are approximately 100 outpatients in whom the indications were registered through the use of DrApp, AFTER the implementation of the drug interactions detection module (Interax-AI). Intervention: Device: Medication Interaction System of Dr App (Interax-AI)	Device: Interax-AI; Interax-AI is a drug interactions detection module for the electronic clinical history software DrApp

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Prevalence of polypharmacy cases detected in outpatients of outpatient clinics of doctors using the electronic medical record application DrApp	Through the electronic medical record called DrApp, the quantity of medicines prescribed to each patient is quantified and used for calculation of polypharmacy prevalence in tha basal period (pre-introduction of Interax-AI) and late period (Post introduction of Interax-AI).	1 year

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Interax-AI associated change in the number of total prescribed drug per patient	Change in total prescribed drug per patient will be calculated as the differene between basal total prescribed drug per patient (Pre-Interax-AI) minus resulting total prescribed drug per patient (Post-Interax-AI)	1 year
Number of total drug interactions per patient and subclassification by severity (in post-Interax-AI period).	The addition of the application called Interax-AI, will allow detecting the presence of drug interactions and their severity in the second phase. These will be reported as the total number of interactions reported per patient, and subclassificated into number of mild (no need to take action), moderate (require patient monitoring), and severe (possible contraindication) interactions detected per patient.	1 year
Difference between Number of total drug interactions per patient in the local environment with those reported in the literature at the international level.	The difference will be calculated as the number of total drug interactions per patient minus the value (number of drug interaction per patient) reported in the bibliography at international level in similar populations.	1 year

Collaborators and Investigators

• Sponsor: University of Buenos Aires
• Collaborators: DrApp S.A.

Study record dates

Study Major Dates

• Study Start (ACTUAL): August 1, 2019
• Primary Completion (ACTUAL): December 1, 2021
• Study Completion (ANTICIPATED): December 1, 2022

Study Registration Dates

• First Submitted: May 7, 2019
• First Submitted That Met QC Criteria: May 7, 2019
• First Posted (ACTUAL): May 9, 2019

Study Record Updates

• Last Update Posted (ACTUAL): May 25, 2022
• Last Update Submitted That Met QC Criteria: May 18, 2022
• Last Verified: May 1, 2022

More Information

Terms related to this study

• Keywords: Outpatient; Polypharmacy; Drug Interaction; Adverse Drug Reaction; DrApp; Interax-AI
• Additional Relevant MeSH Terms: Chemically-Induced Disorders; Drug-Related Side Effects and Adverse Reactions
• Other Study ID Numbers: RB-002

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: There is an intention to publish all the results obtained and share them with other researchers.
• IPD Sharing Time Frame: 1 Year
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; ICF

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No